Image reconstruction from phased-array MRI data based on multichannel blind deconvolution

Authors:
Huajun She;Rang-Rang Chen;Dong Liang;Yuchou Chang;Leslie Ying
Affiliations:
Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT;Department of Electrical and Computer Engineering, University of Utah, Salt Lake City, UT;Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI;Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI;Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

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Abstract

In this paper we consider image reconstruction from multichannel phased array MRI data without prior knowledge of the coil sensitivity functions. A new framework based on multichannel blind deconvolution (MBD) is developed for joint estimation of the image function and the sensitivity functions in k-space. By exploiting the smoothness of the estimated functions in the spatial domain, we develop a regularization approach in conjunction with MBD to obtain good reconstruction of the image function. Experimental results using simulated and real data demonstrate that the proposed reconstruction algorithm can better removes the sensitivity weighting in the reconstructed images compared to the sum-of-squares (SoS) approach.